2008, Volume 10, Issue 5
Strategic Study of CAE >> 2008, Volume 10, Issue 5
Prediction model for residual strength of stiffened panels with multiple site damage based on artificial neural network
1. Postgraduate Team of Naval Aeronautical Engineering Academy, Yantai, Shandong 264001, China;
2. Naval Aeronautical Engineering Academy, Qingdao Branch, Qingdao, Shandong 266041, China
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Abstract
A prediction model for residual strength of stiffened panels with multiple site damage based on artificial neural network (ANN) is developed, and the results obtained from the trained BP model are compared to the analytical and experimental data available in the literature. The results obtained indicate that the neural network model predictions are in the best agreement with the experimental data than any other methods, and the modified linkup models predict better than the linkup model proposed by Swift. In the end several simulations are carried out to predict the trends with varying input parameters. The results show that the residual strength decreases linearly as the half-crack length of lead crack increases and increases linearly as the ligament length increases for both kinds of stiffened panels, but the one-bay stiffened panels are more sensitive to the change than the two-bay stiffened panels.
Keywords
neural network ; multiple site damage ; stiffened panel ; residual strength
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References
[ 1 ] National Transportation Safety Board.Aircraft Accident Report [ R] .Washington D.C.:Report NTSB /AAR -89 /03 ,1989
[ 2 ] Swift T.Widespread fatigue damage monitoring issues and con- cerns [ A] .5th International Conference on Structure Airworthi- ness of New and Aging Aircrat [ C] .Tokyo,1993 link1
[ 3 ] Smith B L, Hijazi A L, Haque A K M, et al.Modified linkup models for determining the strength of stiffened panels with multi- ple site damage [ A] .Proceedings of the FAA /NASA Symposium on the Continued Airworthi - ness of Aircraft Structures [ C ] . Houston, 1999 ,555 -566
[ 4 ] Smith B L, Saville P A, Mouak A, et al.Strength of 2024 -T3 a- luminum panels with multiple site damage [ J] .Journal of Air- craft, 2000 , 37 ( 2 ) : 325 -331 link1
[ 5 ] Alal Hijaxi.Residual Strength of Thin -sheet Aluminum Panels with Multiple Site Damage [ D].Chita: PHD, Wichita State University, 1999
[ 6 ] Ingram J, Kwon Y, Duffe K, et al.Residua strength analysis of skin splices with multiple site damage [ A ] . The 2nd Joint NASA /FAA /-DOD Conference on Aging Aircraft [ C ] .San Francisco, 1998 link1
[ 7 ] Thomson D, Hoadly D, Mchatton J.Load Tests of Flat and Curved Panels with Multiple Cracks [R].Foster Miller Inc,1993
[ 8 ] DeWit R, Fields R, Mordfin L, et al.Fracture behavior of large -scale thin -sheet aluminum alloy [ A] .National Institute of Standards and Technology[ C] .Los Angeles,1995
[ 9 ] Smith B, Mouak A, Savill P, et al.Improved engineering methods for determining the critical ctrength of aluminum panels with mul- tiple site damage [ A] .The 2nd Joint NASA /FAA /DOD Confer- ence on Aging Aircraft [ C] .San Francisco,1988
[10] 袁曾任.人工神经网络及其应用[M].北京:清华大学出版社,1999
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